As computer technologies continue to push the bounds of ever increasing performance and innovation, computer system hardware and software requirements have dramatically increased in complexity and sophistication. This has become even more apparent with the growth of network technologies such as the Internet, for example, wherein ever increasing amounts of data are continually being operated upon, requested, transported, and stored. Other applications such as database managers are also being pushed to handle this increasing traffic of data. One technology that has emerged to transport and process data is XML, which is often referred to as a meta-markup language for text documents. Data can be described in XML documents as strings of text, wherein the actual data is encapsulated by text markup that describes the data. A unit of data and associated markup is defined as an element. Currently, XML defines how elements are delimited by tags, what a tag looks like, what names are acceptable for elements, and where attributes are placed, among other specifications, for example.
The markup in an XML document describes the underlying structure of the document and generally defines which elements are associated with other elements. The markup can also include document semantics. As an example, the markup can indicate that an element is a date, serial number, name or other type of code or designation. As these and other types of elements are transmitted (e.g., XML stream) between systems or databases, changes are often required to be made to existing data due to recently discovered errors in the data or due to the data having changed over time (e.g., person's name or address changing). Since XML merely indicates the most recent state of data, problems can occur as data is transported between databases and/or systems.
In addition to the rise of structured content like XML, relational databases have long been the bulwark of the information infrastructure of countless enterprises. Relational databases provide a primary tool for such enterprises to maintain, access, and analyze data. Such database technologies have evolved over many years and are optimized for accessing and manipulating large information bases. Many businesses, for example, store the majority of their critical information in relational databases. Moreover, many Internet sites manage data employing relational database technology. This approach also makes it possible to develop database search engines for sifting through the large volumes of information that “live” on the Internet. Unlike XML, relational databases are not hierarchically structured but rather are relationally structured to provide efficient management of large amounts of data.
The combination of database technology with self-describing structure of hierarchical languages such as XML opens an interesting perspective for new applications. However, the melding of the kind of tree structures supported by hierarchical languages such as XML with the form of a relational data model presents a number of issues, some of which have already been addressed and solved. One persistent problem that remains, however, relates communications between seemingly inapposite theoretical data constructs. Moreover, in addition to the complexities of communicating between different data structural concepts, new programming models and operating platforms have emerged to support such communications.
As computer science has evolved, object oriented programming has become one of many familiar models designers and programmers utilize to implement functionality within computer systems. The object model generally is defined by a class structure that includes class members providing methods and associated data elements belonging to the class. The class members thus provide/define desired functionality within a computer program, wherein an object is declared as an instance of a particular class. As is commonplace, objects often must exchange data and/or invoke other objects operating on the same platform and/or communicate with objects belonging to remote platforms. In order to communicate between objects, interface systems and standards have been developed to define how objects may communicate and/or interact with one another. A familiar system for communicating and interfacing between objects is known as the Component Object Model (COM), wherein another similar system is referred to as the Common Object Request Brokers Architecture (CORBA). Still yet other communication interfaces may be defined in languages such as JAVA within an operating framework of a Java Virtual Machine, for example. As these and other systems have been developed however, two common object architectures or models generally have emerged and may generally be defined in terms of managed and unmanaged object systems, for example.
Managed objects may be allocated from a heap within a managed software environment and are generally not responsible for managing associated object lifetimes. Managed objects may be described in terms of a data type (e.g., metadata) and automatically collected (e.g., reclaimed) by a managed environment “garbage collector” that removes the object from memory when the object is no longer being accessed. In contrast, unmanaged objects may be allocated from a standard operating system heap, wherein the object itself is responsible for freeing memory it employs when references to the object no longer exist. This may be accomplished through well-known techniques such as reference counting, for example.
As described above, managed objects may be allocated from a managed heap and automatically garbage collected. In order to achieve this, references to managed objects are traced. When a last reference to an object is removed, the garbage collector reclaims the memory occupied by the object mitigating the need to reference count managed objects. Thus, a managed environment essentially handles reference counting internally. Tracing is possible within managed code because the managed environment keeps track of outstanding references that exist on an object. As each new object reference is declared within managed code, the managed environment adds the reference to a list of live references. At any given time, the managed environment, rather than the object itself, is thus aware of live references that exist on a given object. As references fall out of scope or change value, the list of live references is updated, and as long as a reference remains within managed code, the managed environment is able to trace it.
Along with object lifetime management issues described above, managed and unmanaged object systems generally differ in many other significant ways. These differences may include how the object systems provide object interfaces within the respective object systems, how data is structured and/or defined, and how errors and exceptions are handled, for example. Due to these and other differences between managed and unmanaged object systems and the data transformation issues described above, it is presently difficult, time consuming, and expensive in terms of development costs to have objects from an unmanaged system interface and interact with objects from a managed system and visa versa. Moreover, it is generally difficult for managed objects designed according to one object system framework to communicate with objects from an architecturally different managed system framework. This also applies to unmanaged object communications between diverse unmanaged system frameworks.